Getting personal with big data and analytics

During a recent trip to Asia, I met a wise man. He told me that his wife had scrapped her prepaid card because the operator kept spamming her with promotions whenever she got near a shopping mall. As a caring husband and CMO of a large mobile operator he decided to put a stop to this unwanted messaging. He is now challenging his marketing team to work harder and smarter to deliver only personalized and relevant messages. How? By making use of the mass of available data and applying multiple layers of analytics to it. The results thus far are impressive and inspiring in terms of increased response rates and customer satisfaction.

Can you use what you know?

Within the telecommunications industry, we sometimes look to Internet (OTT) players like Amazon with high Net Promoter Scores, which indicate customer satisfaction as well as loyalty and recommendations, in order to benchmark best practices for personalized communications. Both telecom and OTT players have access to big data and one-to-one channels to reach out to their customers. However, the differentiating factor for operators is trust. Many studies report that operators rank soon after police and banks in terms of reliability and trust – an invaluable asset.

Operators possess a wealth of data on locations, movements, services, devices, experiences etc. about their millions of customers, so how can it be utilized without violating privacy and maintaining trust?

Another wise man, this time an EU regulator, at Mobile World Congress in Barcelona made the case for common sense saying that it is high time for us, as a society, to have a discussion on how to use this data and for what purposes. We need to agree on the basics of how to use the data to benefit us all versus when customers need to opt-in – and where never to use it. This discussion is now taking place in many forums but when it comes to ethical questions like this, there are no fast one-size-fits-all solutions.

3 types of use cases

Through discussions with many operators, we’ve observed that there are certain types of situations with related messages that are widely accepted because similar use cases are mentioned repeatedly.

The common denominator of the use cases accepted by the customers and telecommunications seems to revolve around making our lives easier and safer. Big data and analytics use cases which improve network quality and operational efficiency are approved without a doubt. Emergency alerts are also approved without specific consent by the recipients. Illegal messages are, by definition, never authorized and fall under the jurisdiction of local legislation rather than the operator’s. And last, but not least as it is the most frequent use case we have, there is “opt-in”, whereby the mobile subscriber chooses to receive messages about certain services, from certain sources etc. But not all the use cases are clear to judge, and many fall into the grey area in between. What to do when in doubt?

Apply the Golden Rule

The Golden Rule or ethic of reciprocity says that “One should treat others as one would like others to treat oneself”. This principle should also be applied to technology. In the example above, the CMO is challenging his team to treat customers as he would like his wife to be treated.

When exploring the human possibilities of big data and analytics technologies, trust and honesty are the crucial foundation. We need a trusted source to manage and control the data based on rules agreed together. This trusted party could be the mobile operator.

Don’t miss our webinar on: “Big data and predictive analytics: Are you ready to get personal?” on May 27, 2015. Please register here.

Share your thoughts on this topic by replying below – or join the Twitter discussion with @nokianetworks using #NetworksPerform, #mobilebroadband, #CSPCX, #BigData.

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About the author

Miia Toivola

Miia drives Nokia’s global Acquisition & Retention Study. You can also ask her about network management, SON, CEM and analytics. She has 15 years of international experience in telecomms, in Nokia business development, and in product and portfolio management and marketing. Miia has an M.Sc. in Industrial Management from the Helsinki University of Technology and successfully juggles post-graduate studies, family, friends and sports...with a smile.

2 comments

Hitanshu ShahSat 10 October 2015

Great article, Miia!

I am currently working with Alcatel-Lucent (soon Nokia) and have 10+ years of experience in the Telecommunications Industry. I am currently pursuing a certification in Big Data and am very much interested in the confluence of Big Data and Telecommunications which your article addresses.

Which teams in Nokia work with Big Data? Is there a group of people that I can join who have similar interests?

The laws are very clear here: The two companies are not allowed to collaborate on anything until the merger goes through. So we ask for your patience and hope to hear from you again once the deal is closed.